Altering the past to influence the future: the effect of mental unpacking on past evaluations and future preferences

Consumers use affective evaluations of past hedonic experiences in their future decision-making. However, past evaluations such as how enjoyable the experience was may be hard to retrieve, and consumers tend to recall what they did (i.e. the constituent activities of the prior experience) in order to reconstruct them. It is proposed here that recalling these constituent activities in a packed versus unpacked fashion will distort both the reconstruction process and its outcome. Results from two experiments show that mental unpacking interacted with experience enjoyment to alter past evaluations in two ways: if the enjoyment of the experience was high, unpacked recalls increased remembered enjoyment, but unpacking decreased remembered enjoyment if the experience enjoyment was low. Finally, mediation analysis indicated that the unpacking by enjoyment interaction distorted future preferences through the mediating role of remembered enjoyment.     

Response style corrected market segmentation for ordinal data

Survey data collected for market segmentation studies is typically ordinal in nature. As such, it is susceptible to response styles. Ignoring response styles can lead to market segments which do not differ in beliefs, but merely in how segment members use survey answer options and which possibly occur in addition to the belief segments. We propose a finite mixture model which simultaneously segments and corrects for response styles, permits heterogeneity in both beliefs and response styles, accommodates a range of different response styles, does not impose a certain relationship between the response style and belief segments, and is suitable for ordinal data. The performance of the model is tested using both artificial and empirical survey data.     

A Sample Survey Based Linguistic MADM Method with Prospect Theory for Online Shopping Problems

In MADM problems, the attributes are often rated in linguistic variables, some researchers transform them into numerical values through some formulas. However, it might be inconsistent with real human thinking in some extent. In order to deal with such problems, a sample survey based MADM method with prospect theory is proposed. Firstly, through sampling survey, we collect the data in single point format corresponding to the words, and establish the codebook by mapping words into fuzzy sets, after that fuzzy operation rules are suitable for them. Secondly, based on the reference points, the gain and/or loss matrix is obtained, in accordance with the value function, the prospect value matrix is constructed. Finally, if the attributes are independent, the weighted prospect value of each alternative is computed, if the attributes are dependent, the Choquet integral based prospect value of each alternative is computed. The alternatives are ranked in descending order respect to the defuzzified values. The first alternative is chosen as the best decision result. The feasibility of the proposed method is illustrated through an application in online shopping problem from real life.     

A Sealed-Bid Two-Attribute Yardstick Auction Without Prior Scoring

We analyze a two-attribute single item procurement auction that uses yardstick competition to settle prices. The auction simplifies the procurement process by reducing the principal’s articulation of preferences to simply choosing the most preferred offer as if it was a market with posted prices. This is done simply by replacing the submitted sealed bids by yardstick bids, computed by a linear weighting of the other participants’ bids. We show that there is only one type of Nash equilibria where some agents may win the auction by submitting a zero price-bid. Using a simulation study we demonstrate that following this type of equilibrium behavior often leads to winner’s curse. The simulations show that in auctions with more than 12 participants the chance of facing winner’s curse is around 95 %. Truthful reporting, on the other hand, does not constitute a Nash equilibrium but it is ex post individually rational. Using a simulation study we demonstrate that truthful bidding may indeed represent some kind of focal point.     

Multiple Attribute Group Decision Making Method Based on Utility Theory Under Interval-Valued Intuitionistic Fuzzy Environment

In this paper, a kind of multiple attribute group decision making problem is studied, where there is no original information about the weights of importance of the attributes and the decision makers (DMs), and the attribute values are given in the form of interval-valued intuitionistic fuzzy numbers (IVIFNs). To solve this problem, a new method is proposed based on utility theory. In the proposed method, the weights of importance of the DMs and the attributes are all determined by using the intuitionistic indexes of related IVIFNs. And then, the alternatives are compared by using their composite interval indexes which are generated based on utility theory. Finally, two numerical examples are proposed to demonstrate the effectiveness of the proposed method.     

GAMBLING IN CONTESTS WITH REGRET

This paper discusses the gambling contest introduced in Seel and Strack (2013, Gambling in Contests, Journal of Economic Theory, 148(5), 2033–2048) and considers the impact of adding a penalty associated with failure to follow a winning strategy. The Seel and Strack model consists of n‐agents each of whom privately observes a transient diffusion process and chooses when to stop it. The player with the highest stopped value wins the contest, and each player's objective is to maximize her probability of winning the contest. We give a new derivation of the results of Seel and Strack based on a Lagrangian approach. Moreover, we consider an extension of the problem to a behavioral finance context in the sense of regret theory. In particular, an agent is penalized when her chosen strategy does not win the contest, but there existed an alternative strategy that would have resulted in victory.     

Does hospitality diversity education make a difference in undergraduate students’ emotional intelligence

Soft skills are typically referred to as the attributes exhibited or contained by an individual that display his/her ability to interact with others. Two types of soft skills that are often discussed within the hospitality industry are diversity awareness and emotional intelligence. Diversity may be explained or defined as a state of unlikeness, the conditions of being different, and all things that make us different. Areas where differences may exist include race, ethnicity, gender, sexual orientation, socio-economic status, age, physical abilities, religious beliefs, political affiliation and emotional reaction. Emotional intelligence (EI) has been defined as the ability to perceive, understand, regulate, and harness emotions in the self and others. How one deals with emotion is one characteristic that varies from culture to culture. Research has shown that EI may be a contributing factor in a moment of truth being considered a failure or success. The purpose of this study was to examine if undergraduate student EI scores change after completing a diversity issues course. Students completed the Assessing Emotions Scale on the first class day. At the conclusion of the 15-week course covering approximately 20 diversity issues concepts students completed the same EI assessment. Paired sampled t-testing was conducted to determine whether mean differences existed when comparing post and pre-course scores. Results of this study suggest that certain components of EI are significantly changed after taking the diversity issues course.     

The Business Economist’s Toolkit

Business economists are not members of the high church of academic orthodoxy. Our tool kit includes research functions, such as business cycle analysis, demographics research, data analytics, primary research, diversity of thought, and client research. It also includes personal skills that should be cultivated and practiced, such as curiosity, maintaining a nonpartisan view, humility, courage, and effective communication.     

Bayesian and Bühlmann credibility for phase-type distributions with a univariate risk parameter

Credibility theory is a statistical tool to calculate the premium for the next period based on past claims experience and the manual rate. Each contract is characterized by a risk parameter. A phase-type (or PH) random variable, which is defined as the time until absorption in a continuous-time Markov chain, is fully characterized by two sets of parameters from that Markov chain: the initial probability vector and transition intensity matrix. In this article, we identify an interpretable univariate risk parameter from amongst the many candidate parameters, by means of uniformization. The resulting density form is then expressed as an infinite mixture of Erlang distributions. These results are used to obtain a tractable likelihood function by a recursive formula. Then the best estimator for the next premium, i.e. the Bayesian premium, as well as its approximation by the Bühlmann credibility premium are calculated. Finally, actuarial calculations for the Bühlmann and Bayesian premiums are investigated in the context of a gamma prior, and illustrated by simulated data in a series of examples.